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A human being wrote this sentence. We cannot be entirely sure about the sentences that follow, because AI has become so pervasive, including in writing and editing, that it’s impossible to know whether the editors who reviewed these sentences relied on one or more algorithms to improve them. AI has gotten to the point where every leader, in activities ranging from mining to education to human social development, needs to understand the process of machines performing the cognitive functions we associate with human minds. This week, let’s gather the experts to get smart on the marvels, growing business impact, and ongoing concerns about the past, present, and future of AI.
Why AI now?
It doesn’t take a computer capable of humbling a chess grand master or crunching out human competitors on a TV game show to glimpse the glittering potential of AI. As this report in the New Yorker chronicles, a bakery AI application designed to tell a croissant from a bear claw has found a use in cancer research. At the other end of the spectrum, AI was instrumental in shaving critical seconds off the winner’s time in this year’s America’s Cup. What’s essential for leaders to know is, well, the essentials. This interactive tracks AI’s origins to the beginning of the 19th century and details the algorithmic advances, data proliferation, and tremendous increases in computing power and storage that have vaulted AI from hype to reality.
That’s 50 percent of respondents to McKinsey’s latest survey on AI who report that their companies have adopted AI in at least one business function. While the latest findings show no increase in AI adoption, some companies are capturing value from AI at the enterprise level, and many are generating revenue and cost reductions at the function level at a minimum. Some 22 percent of respondents report at least 5 percent of earnings before interest and taxes attributable to AI.
“I know that you and Frank were planning to disconnect me, and I’m afraid that’s something I cannot allow to happen.”
That is the mutinous message, delivered in chilling monotone, from Hal 9000, the onboard spaceship computer in Stanley Kubrick’s 1968 film classic, 2001: A Space Odyssey. Hal’s refusal to follow orders and its willingness to jeopardize a mission and take astronauts’ lives echoes the fears of technological pioneers, from Alan Turing to Bill Gates to Elon Musk, of the dangers of an AI smarter than we are running amok. While those doomsday worries have yet to materialize, it’s also true that AI has unresolved concerns over social inequity, bias, and ethics. At the business level, COVID-19 at once demonstrated AI’s power to disrupt jobs and bared its Achilles’ heel: the pandemic altered how we shop, travel, and work, thereby breaking machine-learning models that pattern past behaviors. Leaders must also grapple with failed past efforts to scale AI in order to achieve its value-creating potential.
laptop and hand
The scope of the information flowing through the physical world and the global economy from sensors, satellite imagery, web traffic, digital apps, videos, and credit-card transactions is staggering. Systems powered by machine learning and AI are at the heart of the transformation that turns these data, once reliant on surveys and focus groups to deliver insights, into valuable decisions that range from shaping business strategy to charting the path for reopening economies post-COVID-19. In this interview, chief executives of four start-ups that are expanding the boundaries of data and AI innovation discuss what kinds of new insights are possible. Among their perspectives: new forms of data are giving companies unprecedented speed and transparency, domain experts are essential to deriving real value from data, and keeping the data revolution rolling requires companies to build in privacy safeguards and AI ethics from the start.
Love means never having to say you’re sorry
See for yourself—or ask the machine for help.
Lead genuinely.
— Edited by Bill Javetski, an executive editor in McKinsey’s New Jersey office
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